Skip to main content

Advertisement

SpringerLink
Log in

Interactive Technologies for Autistic Children: A Review

  • Published:
Cognitive Computation Aims and scope Submit manuscript

Abstract

Recently, there have been considerable advances in the research on innovative information communication technology (ICT) for the education of people with autism. This review focuses on two aims: (1) to provide an overview of the recent ICT applications used in the treatment of autism and (2) to focus on the early development of imitation and joint attention in the context of children with autism as well as robotics. There have been a variety of recent ICT applications in autism, which include the use of interactive environments implemented in computers and special input devices, virtual environments, avatars and serious games as well as telerehabilitation. Despite exciting preliminary results, the use of ICT remains limited. Many of the existing ICTs have limited capabilities and performance in actual interactive conditions. Clinically, most ICT proposals have not been validated beyond proof of concept studies. Robotics systems, developed as interactive devices for children with autism, have been used to assess the child’s response to robot behaviors; to elicit behaviors that are promoted in the child; to model, teach and practice a skill; and to provide feedback on performance in specific environments (e.g., therapeutic sessions). Based on their importance for both early development and for building autonomous robots that have humanlike abilities, imitation, joint attention and interactive engagement are key issues in the development of assistive robotics for autism and must be the focus of further research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. a very simple language based on a list of simple everyday words, which uses speech, gesture, facial expression, body language, signs, symbols and words to aid communication.

  2. When the child pushes one of the buttons, the robot blows bubbles while turning in place. When the child does not push one of the buttons, the robot does nothing (no bubbles, no turning).

References

  1. Aleotti J, Caselli S. Robust trajectory learning and approximation for robot programming by demonstration. Rob Auton Syst. 2006;54(5):409–13.

    Article  Google Scholar 

  2. Altmann U. Studying movement synchrony using time series and regression models. In: Esposito IA, Hoffmann R, Hübler S, Wrann B, editors. Program and Abstracts of the COST 2102. International training school on cognitive behavioural systems. Dresden, Germany, 21–25 February; 2011. p. 23.

  3. Andry P, Gaussier P, Moga S, Banquet J, Nadel J. Learning and communication in imitation: an autonomous robot perspective. IEEE Trans Syst Man Cybernet Part A. 2001;31(5):431–44.

    Article  Google Scholar 

  4. Andry P, Gaussier P, Nadel J, Hirsbrunner B. Learning invariant sensory-motor behaviors : a developmental approach of imitation mechanisms. Adapt Behav, 2004;12(2):117–40.

  5. Ashenfelter K, Boker S, Waddell J, Vitanov N, Abadjieva E. Spatiotemporal symmetry and multifractal structure of head movements during dyadic conversation. J Exp Psychol Hum Percept Perform. 2009;35(4):1072.

    Article  PubMed  Google Scholar 

  6. Bakker P, Kuniyoshi Y. Robot see, robot do: an overview of robot imitation. In: AISB96 Workshop on Learning in Robots and Animals. 1996; p. 3–11.

  7. Baldwin J. Development and evolution. New York: The Macmillan company; 1902.

  8. Baron-Cohen S. Mindblindness: an essay on autism and theory of mind. Cambridge: MIT press; 1997.

    Google Scholar 

  9. Baron-Cohen S, Wheelwright S. ’Obsessions’ in children with autism or asperger syndrome. Content analysis in terms of core domains of cognition. Br J Psychiatry. 1999;175(5):484–90.

    Article  CAS  PubMed  Google Scholar 

  10. Bashshur R. Telemedicine and health care. Telemed J E Health. 2002;8(1):512.

    Google Scholar 

  11. Bauminger N, Gal E, Goren-Bar D. Enhancing social communication in high functioning children with autism through a co-located interface. 6th International Workshop on Social Intelligence Design, Trento 2007.

  12. Bekele E, Zheng Z, Swanson A, Crittendon J, Warren Z, Sarkar N. Understanding how adolescents with autism respond to facial expressions in virtual reality environments. IEEE Trans Vis Comput Graph. 2013;19(4):711–20.

    Article  PubMed  Google Scholar 

  13. Bellani M, Fornasari L, Chittaro L, Brambilla P. Virtual reality in autism: state of the art. Epidemiol Psychiatr Sci. 2011;20(3):235–8.

    Article  CAS  PubMed  Google Scholar 

  14. Bernieri F, Reznick J, Rosenthal R. Synchrony, pseudosynchrony, and dissynchrony:measuring the entrainment process in mother-infant interactions. J Personal Soc Psychol. 1988;54(2):243.

    Article  Google Scholar 

  15. Berthouze L, Bakker P, Kuniyoshi Y. Learning of oculo-motor control: a prelude to robotic imitation. In: Intelligent Robots and Systems’ 96, IROS 96, Proceedings of the 1996 IEEE/RSJ International Conference on, vol. 1. 1996; p. 376–381. IEEE.

  16. Billard A, Hayes G. Learning to communicate through imitation in autonomous robots. In: Artificial Neural NetworksICANN’97. Springer, Berlin; 1997; p. 763–768.

  17. Bird G, Leighton J, Press C, Heyes C. Intact automatic imitation of human and robot actions in autism spectrum disorders. Proc R Soc B Biol Sci. 2007;274(1628):3027–31.

    Article  Google Scholar 

  18. Blocher K, Picard R. Affective social quest: emotion recognition therapy for autistic children. Socially Intelligent Agents: creating relationships with computers and robots; 2002. p. 133140 .

  19. Boker S, Xu M, Rotondo J, King K. Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series. Psychol Methods. 2002;7(3):338–55.

    Article  PubMed  Google Scholar 

  20. Boucenna S, Anzalone S, Tilmont E, Cohen D, Chetouani M. Learning of social signatures through imitation game between a robot and a human partner. IEEE Trans Auton Ment Dev, in revision ; 2014a.

  21. Boucenna S, Delaherche E, Chetouani M, Gaussier P. A new approach for learning postures : an imitation game between a human and a robot. In: IEEE/RSJ International Conference on Robots and Systems, (IROS 2012). Workshop : Cognitive Neuroscience, Robotics; 2012. p. 1–4.

  22. Boucenna S, Gaussier P, Andry P, Hafemeister L. Imitation as a communication tool for online facial expression learning and recognition. In: Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE. 2010; p. 5323–5328.

  23. Boucenna S, Gaussier P, Andry P, Hafemeister L. A robot learns the facial expressions recognition and face/non-face discrimination through an imitation game. Int J Soc Robot, to appear 2014b.

  24. Boucenna S, Gaussier P, Hafemeister L. Development of joint attention and social referencing. In: Development and Learning (ICDL), 2011 IEEE International Conference on, vol 2. IEEE. 2011; p. 1–6.

  25. Calinon S, Guenter F, Billard A. On learning, representing, and generalizing a task in a humanoid robot. IEEE Trans Syst Man Cybernet Part B Cybernet. 2007;37(2):286–98.

    Article  Google Scholar 

  26. Campbell C, Peters R, Bodenheimer R, Bluethmann W, Huber E, Ambrose R. Superpositioning of behaviors learned through teleoperation. IEEE Trans Robot. 2006;22(1):79–91.

    Article  Google Scholar 

  27. Campbell N. Multimodal processing of discourse information; the effect of synchrony. In: Universal Communication, 2008. ISUC’08. Second International Symposium on. IEEE, 2008; p. 12–15.

  28. Carpendale J, Lewis C. Constructing an understanding of the mind: the development of children’s social understanding within social interaction. Behav Brain Sci. 2004;27:79–151.

    PubMed  Google Scholar 

  29. Carpenter M, Nagell K, Tomasello M. Social cognition, joint attention, and communicative competence from 9 to 15 months of age. Monogr Soc Res Child Dev. 1998;63(4):i–vi, 1–143.

  30. Chaby L, Chetouani M, Plaza M, Cohen D. Exploring multimodal social-emotional behaviors in autism spectrum disorders. In: Workshop on Wide Spectrum Social Signal Processing, 2012 ASE/IEEE International Conference on Social, Computing. 2012; p. 950–954.

  31. Chaminade T, Da Fonseca D, Rosset D, Lutcher E, Cheng G, Deruelle C. Fmri study of young adults with autism interacting with a humanoid robot. In: RO-MAN, 2012 IEEE. IEEE, 2012; p. 380–385.

  32. Chetouani M, Mahdhaoui A, Ringeval F. Time-scale feature extractions for emotional speech characterization. Cognit Comput. 2009;1(2):194–201.

    Article  Google Scholar 

  33. Cohen D. Traumatismes et traces : donnés expérimentales. Neuropsychiatr Enfance Adolesc. 2012;60:315–23.

    Article  Google Scholar 

  34. Costa S, Santos C, Soares F, Ferreira M, Moreira F. Promoting interaction amongst autistic adolescents using robots. In Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. IEEE; 2010; p. 3856–3859.

  35. Damasio A. Descartes’ error. New York: Putnam’s Sons; 1994.

    Google Scholar 

  36. Dautenhahn K. Roles and functions of robots in human society: implications from research in autism therapy. Robotica. 2003;21(4):443–52.

    Article  Google Scholar 

  37. Dautenhahn K, Werry I. Towards interactive robots in autism therapy: Background, motivation and challenges. Pragmat Cognit. 2004;12(1):1–35.

    Article  Google Scholar 

  38. Dawson G, Rogers S, Munson J, Smith M, Winter J, Greenson J, Donaldson A, Varley J. Randomized, controlled trial of an intervention for toddlers with autism: the early start denver model. Pediatrics. 2009;125(1):17–23.

    Article  Google Scholar 

  39. de Rengervé A, Boucenna S, Andry P, Gaussier P. Emergent imitative behavior on a robotic arm based on visuo-motor associative memories. In: Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE, 2010; p. 1754–1759.

  40. Decety J, Jackson P. The functional architecture of human empathy. Behav Cogn Neurosci Rev. 2004;3(2):71–100.

    Article  PubMed  Google Scholar 

  41. Delaherche E, Chetouani M. Multimodal coordination: exploring relevant features and measures. In: Proceedings of the 2nd international workshop on Social signal processing. ACM: 2010; p. 47–52.

  42. Delaherche E, Chetouani M, Mahdhaoui A, Saint-Georges C, Viaux S, Cohen D. Interpersonal synchrony: a survey of evaluation methods across disciplines. IEEE Trans Affect Comput. 2012;3(3):349–65.

    Article  Google Scholar 

  43. Diamond B, Shreve G, Bonilla J. Telerehabilitation, cognition and user-accessibility. NeuroRehabilitation. 2003;18(2):1717.

    Google Scholar 

  44. Diehl J, Schmitt L, Villano M, Crowell C. The clinical use of robots for individuals with autism spectrum disorders: a critical review. Res Autism Spectr Disord. 2012;6(1):249–62.

    Article  PubMed Central  PubMed  Google Scholar 

  45. Dillmann R. Teaching and learning of robot tasks via observation of human performance. Robot Auton Syst. 2004;47(2):109–16.

    Article  Google Scholar 

  46. DiSalvo D, Oswald D. Peer-mediated interventions to increase the social interaction of children with autism: consideration of peer experiences. Focus Autism Other Dev Disabl. 2002;17(4):198–208.

    Article  Google Scholar 

  47. Duquette A, Michaud F, Mercier H. Exploring the use of a mobile robot as an imitation agent with children with low-functioning autism. Auton Robots. 2008;24(2):147–57.

    Article  Google Scholar 

  48. Eddon G. Danny’s rooms. In: proceedings of the john hopkins national search for computing applications to assist persons with disabilities. IEEE Computing Society press, 1992; p. 7879.

  49. Emery N. The eyes have it: the neuroethology, function and evolution of social gaze. Neurosci Biobehav Rev. 2000;24(6):581–604.

    Article  CAS  PubMed  Google Scholar 

  50. Enyon A. Computer interaction: an update on the avatar program. Communication, Summer. 1997; p. 18.

  51. Esposito A. The perceptual and cognitive role of visual and auditory channels in conveying emotional information. Cognit Comput. 2009;1(3):268–78.

    Article  Google Scholar 

  52. Fabri M. Emotionally expressive avatars for collaborative virtual environments. A thesis submitted in partial fulfillment of the requirements of Leeds Metropolitan University for the degree of Doctor of Philosophy 2006.

  53. Fabri M, Elzouki S, Moore D. Emotionally expressive avatars for chatting, learning and therapeutic intervention, human–computer interaction. HCI Intelligent Multimodal Interaction Environments, 2007; p. 275–285.

  54. Feil-Seifer D, Matarić M. Toward socially assistive robotics for augmenting interventions for children with autism spectrum disorders. In: Experimental robotics. Springer, Berlin. 2009; p. 201–210.

  55. Feil-Seifer D, Mataric M. Automated detection and classification of positive vs. negative robot interactions with children with autism using distance-based features. In: Human-Robot Interaction (HRI), 2011 6th ACM/IEEE International Conference on. IEEE: 2011; p. 323–330.

  56. Flores M, Musgrove K, Renner S, Hinton V, Strozier S, Franklin S, Hil D. A comparison of communication using the apple ipad and a picture-based system. Augment Altern Commun. 2012;28(2):74–84.

    Article  PubMed  Google Scholar 

  57. Fong T, Nourbakhsh I, Dautenhahn K. A survey of socially interactive robots. Robo Auton Syst. 2003;42(3):143–66.

    Article  Google Scholar 

  58. François D, Powell S, Dautenhahn K. A long-term study of children with autism playing with a robotic pet: taking inspirations from non-directive play therapy to encourage children’s proactivity and initiative-taking. Interact Stud. 2009;10(3):324–73.

    Article  Google Scholar 

  59. Frith U, Morton J, Leslie A. The cognitive basis of a biological disorder: autism. Trends Neurosc. 1991;14(10):434438.

    Article  Google Scholar 

  60. Fujimoto I, Matsumoto T, De Silva P, Kobayashi M, Higashi M. Mimicking and evaluating human motion to improve the imitation skill of children with autism through a robot. Int J Soc Robot. 2011;3(4):349–57.

    Article  Google Scholar 

  61. Gal E, Goren-Bar D, Gazit E, Bauminger N, Cappelletti A, Pianesi F, Stock O, Zancanaro M, Weiss PL. Enhancing social communication through story-telling among high-functioning children with autism. Intelligent Technologies for Interactive Entertainment, 2005; p. 320–323.

  62. Golan O, Ashwin E, Granader Y, McClintock S, Day K, Leggett V, Baron-Cohen S. Enhancing emotion recognition in children with autism spectrum conditions: an intervention using animated vehicles with real emotional faces. J Autism Dev Disord. 2010;40(3):269–79.

    Article  PubMed  Google Scholar 

  63. Gonzalez J, Cabrera M, Gutierrez F. Using videogames in special education. Comput Aid Syst Theory, EUROCAST. 2007; p. 360–7.

  64. Green, S. (1993). Computer-based simulations in the education and assessment of autistic children. in: Rethinking the Roles of Technology in Education, Tenth International Conference on Technology and Education, Massachusetts Institute of Technology, Cambridge, MA, 1:334336.

  65. Guenter F, Hersch M, Calinon S, Billard A. Reinforcement learning for imitating constrained reaching movements. Adv Robot. 2007;21(13):1521–44.

    Google Scholar 

  66. Hayes G, Demiris J. A robot controller using learning by imitation. Department of Artificial Intelligence, University of Edinburgh; 1994.

  67. Herrera G, Alcantud F, Jordan R, Blanquer A, Labajo A, De pablo C. Development of symbolic play through the use of virtual reality tools in children with autistic spectrum disorders. Autism. 2008;12:143157.

    Article  Google Scholar 

  68. Hersch M, Guenter F, Calinon S, Billard A. Dynamical system modulation for robot learning via kinesthetic demonstrations. IEEE Trans Robot. 2008;24(6):1463–7.

    Article  Google Scholar 

  69. Hetzroni O, Juman T. Effects of a computer-based intervention program on the communicative functions of children with autism. J Autism Dev Disord. 2011;34(2):95–113.

    Article  Google Scholar 

  70. Hileman C. Computer technology with autistic children. In: Autism Society of America National Conference. Milwaukee, Wisconsin; 1996.

  71. Hopkins I, Gower M, Perez T, Smith D, Amthor F, Wimsatt F, Biasini F. Avatar assistant: improving social skills in students with an asd through a computer-based intervention. J Autism Dev Disord. 2011;41(11):1543–55.

    Article  PubMed  Google Scholar 

  72. Horace H, Belton K. Smart ambience games for children with learning difficultie s. Technol E Learn Digit Entertain, 2006; 484–493.

  73. Howlin P, Baron-Cohen S, Hadwin J. Teaching children with autism to mind-read: a practical guide for teachers and parents. New York: Wiley; 1999.

    Google Scholar 

  74. Hutinger P, Rippey R. How five preschool children with autism responded to computers. 1997.

  75. Ijspeert A, Nakanishi J, Schaal S. Movement imitation with nonlinear dynamical systems in humanoid robots. In: Robotics and Automation, 2002. Proceedings. ICRA’02. IEEE International Conference on, vol 2. IEEE; 2002; pages 1398–1403.

  76. Jones S. Imitation in infancy the development of mimicry. Psychol Sci. 2007;18(7):593–9.

    Article  PubMed  Google Scholar 

  77. Jones S. The development of imitation in infancy. Philos Trans R Soc B Biol Sci. 2009;364(1528):2325.

    Article  Google Scholar 

  78. Jordan R. Computer assisted education for individuals with autism. Paper presented at the Autisme France 3rd International Conference 1995.

  79. Jordan R. Multidisciplinary work for children with autism. Educ Child Psychol. 2001;18(2):5–14.

    Google Scholar 

  80. Jowett E, Moore D, Anderson A. Using an ipad-based video modelling package to teach numeracy skills to a child with an autism spectrum disorder. Dev Neurorehabil. 2012;15(4).

  81. Kagohara D, van der Meer L, Ramdoss S, O’Reilly M, Lancioni G, Davis T, Rispoli M, Lang R, Marschik P, Sutherland D, Green V, Sigafoos J. Using ipods and ipads in teaching programs for individuals with developmental disabilities: a systematic review. Res Dev Disabil. 2013;34(1):147–56.

    Article  PubMed  Google Scholar 

  82. Kaliouby R, Picard R, Barron-Cohen S. Affective computing and autism. Ann N Y Acad Sci, 2006; P. 228248.

  83. Kaplan F, Hafner V. The challenges of joint attention. Interact Stud. 2006;7(2):135–69.

    Article  Google Scholar 

  84. Konstantinidis E, Bamidis P, Koufogiannis D. Development of a generic and flexible human body wireless sensor network. In Proceedings of the 6th European Symposium on Biomedical Engineering (ESBME) 2008.

  85. Konstantinidis E, Luneski A, Frantzidis C, Pappas C, Bamidis P. A proposed framework of an interactive semi-virtual environment for enhanced education of children with autism spectrum disorders. The 22nd IEEE International Symposium on Computer-Based Medical Systems (CBMS) 2009.

  86. Kozima H, Michalowski M, Nakagawa C. Keepon: a playful robot for research, therapy, and entertainment. Int J Soc Robot. 2009;1(1):3–18.

    Article  Google Scholar 

  87. Kozima H, Nakagawa C, Yasuda Y. Children-robot interaction: a pilot study in autism therapy. Prog Brain Res. 2007;164:385.

    Article  PubMed  Google Scholar 

  88. Kuniyoshi Y. The science of imitation-towards physically and socially grounded intelligence. In: Special Issue TR-94001, Real World Computing Project Joint Symposium, Tsukuba-shi, Ibaraki-ken. Citeseer; 1994.

  89. Lányi CS, Tilinger A. Multimedia and virtual reality in the rehabilitation of autistic children. In: Computers helping people with special needs. Heidelberg: Springer; 2004. p. 22–8.

  90. Liu C, Conn K, Sarkar N, Stone W. Physiology-based affect recognition for computer-assisted intervention of children with autism spectrum disorder. Int J Hum Comput Stud. 2008;66(9):662–77.

    Article  Google Scholar 

  91. Lum P, Uswatte G, Taub E. A telerehabilitation approach to delivery of constraint-induced movement therapy. J Rehabil R D. 2006;43(3):391400.

    Google Scholar 

  92. Luneski, A., Konstantinidis, E., Hitoglou-Antoniadou, M., and Bamidis, P. (2008). Affective computer-aided learning for autistic children. 1st Workshop of Child, Computer and Interaction (WOCCI 08). Chania, Greece.

  93. Marin-Urias L, Sisbot E, Alami R. Geometric tools for perspective taking for human-robot interaction. In: Artificial Intelligence, 2008. MICAI’08. Seventh Mexican International Conference on. IEEE; 2008; p. 243–249.

  94. Marin-Urias L, Sisbot E, Pandey A, Tadakuma R, Alami R. Towards shared attention through geometric reasoning for human robot interaction. In: Humanoid Robots, 2009. Humanoids 2009. 9th IEEE-RAS International Conference on. IEEE; 2009; p. 331–336.

  95. Marnik J, Szela M. Multimedia program for teaching autistic children. Inf Technol Biomed ASC. 2008;47:505512.

    Google Scholar 

  96. Maurer A, Hersch M, Billard A. Extended hopfield network for sequence learning: Application to gesture recognition. In: Artificial Neural Networks: Biological Inspirations-ICANN 2005. Springer, Berlin; 2005; p. 493–498.

  97. Michelet S, Karp K, Delaherche E, Achard C, Chetouani M. Automatic imitation assessment in interaction. In: Human Behavior Understanding (IROS’12 workshop)., page To appear 2012.

  98. Mitchell P, Parsons S, Leonard A. Using virtual environments for teaching social understanding to 6 adolescents with autistic spectrum disorders. J Autism Dev Disord. 2006;3(37):589–600.

    Google Scholar 

  99. Mitchell P, Parsons S, Leonard A. Using virtual environments for teaching social understanding to 6 adolescents with autistic spectrum disorders. J Autism Dev Disord. 2007;37:589600.

    Google Scholar 

  100. Murdock L, Ganz J, Crittendon J. Use of an ipad play story to increase play dialogue of preschoolers with autism spectrum disorders. J Autism Dev Disord. 2013;43(9):2174–89.

    Article  PubMed  Google Scholar 

  101. Murray D. Autism and information technology: therapy with computers. Autism Learn Guide Good Pract, 1997; p. 100117.

  102. Nadel J, Simon M, Canet P, Soussignan R, Blancard P, Canamero L, Gaussier P. Human responses to an expressive robot. In: Procs of the Sixth International Workshop on Epigenetic Robotics. Lund University; 2006.

  103. Nagai Y, Hosoda K, Morita A, Asada M. A constructive model for the development of joint attention. Connect Sci. 2003;15(4):211–29.

    Article  Google Scholar 

  104. Narzisi A, Colombi C, Fusar P, Balottin U, Muratori F. Non-pharmacological treatments in autism spectrum disorders: an overview on early interventions for pre-schoolers. Curr Clin Pharmacol. 2014;9(1):1–10.

    Article  Google Scholar 

  105. Narzisi A, Muratori F, Calderoni S, Fabbro F, Urgesi C. Neuropsychological profile in high functioning autism spectrum disorders. J Autism Dev Dis. 2013;43(8):1895–909.

  106. Orvalho V, Miranda J, Sousa A. Facial synthesys of 3d avatars for therapeutic applications. Stud Health Technol Inform. 2009;144:96–8.

    PubMed  Google Scholar 

  107. Ospina M, Seida J, Clark B, Karkhaneh M, Hartling L, Tjosvold L, Vandermeer B, Smith V. Behavioural and developmental interventions for autism spectrum disorder: a clinical systematic review. PLoS One, 2008;3(11).

  108. Papert S. Mindstorms: Children, computers, and powerful ideas. New York: Basic Books Inc; 1980.

    Google Scholar 

  109. Pardowitz M, Dillmann R. Towards life-long learning in household robots: The piagetian approach. In: Development and Learning, 2007. ICDL 2007. IEEE 6th International Conference on. IEEE; 2007; p. 88–93.

  110. Pardowitz M, Knoop S, Dillmann R, Zollner R. Incremental learning of tasks from user demonstrations, past experiences, and vocal comments. IEEE Trans Syst Man Cybernet Part B Cybernet. 2007;37(2):322–32.

    Article  Google Scholar 

  111. Parmanto B, Saptono A, Ferrydiansyah R, Sugiantara I. Transcoding biomedical information resources for mobile handhelds. Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS’05). IEEE Computer Society, 2005;6:151–158.

  112. Parsons S, Beardon L, Neale H, Reynard G, Eastgate R, Wilson J, Cobb S, Benford S, Mitchell P, Hopkins E. Development of social skills amongst adults with asperger’s syndrome using virtual environments: the ’as interactive’ project. In: Sharkey P, Cesarani A, Pugnetti L, Rizzo A, editors. 3rd ICDVRAT. Sardinia Italy: University of Reading; 2000.

    Google Scholar 

  113. Parsons S, Leonard A, Mitchell P. Virtual environments for social skills training: comments from two adolescents with autistic spectrum disorder. Comput Educ. 2006;47(2):186–206.

    Article  Google Scholar 

  114. Piaget J. La naissance de l’intelligence chez l’enfant, vol. 968. Paris: Delachaux et Niestlé; 1977.

    Google Scholar 

  115. Picard R. Emotion research by the people, for the people. Emot Rev. 2010;2(3):250–4.

    Article  Google Scholar 

  116. Pierno A, Mari M, Lusher D, Castiello U. Robotic movement elicits visuomotor priming in children with autism. Neuropsychologia. 2008;46(2):448–54.

    Article  PubMed  Google Scholar 

  117. Pioggia G, Igliozzi R, Ferro M, Ahluwalia A, Muratori F, De Rossi D. An android for enhancing social skills and emotion recognition in people with autism. IEEE Trans Neural Syst Rehabil Eng. 2005;13(4):507–15.

    Article  PubMed  Google Scholar 

  118. Pioggia G, Igliozzi R, Sica M, Ferro M, Muratori F, Ahluwalia A, De Rossi D. Exploring emotional and imitational android-based interactions in autistic spectrum disorders. J Cyber Therapy Rehabil. 2008;1(1):49–61.

    Google Scholar 

  119. Premack D, Woodruff G. Does the chimpanzee have a theory of mind? Behav Brain Sci. 1978;1(04):515–26.

    Article  Google Scholar 

  120. Rajendran G, Mitchell P. Computer mediated interaction in asperger’s syndrome: the bubble dialogue program. Comput Educ. 2000;35:187–207.

    Article  Google Scholar 

  121. Ramseyer F, Tschacher W. Nonverbal synchrony in psychotherapy: coordinated body-movement reflects relationship quality and outcome. J Consult Clin Psychol. 2011;79(3):284–95.

    Article  PubMed  Google Scholar 

  122. Ravindra P, De Silva S, Tadano K, Saito A, Lambacher S, Higashi M. Therapeutic-assisted robot for children with autism. In: Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on. IEEE; 2009; p. 3561–3567.

  123. Ricks D, Colton M. Trends and considerations in robot-assisted autism therapy. In: Robotics and Automation (ICRA), 2010 IEEE International Conference on. IEEE; 2010; p. 4354–4359.

  124. Robins B, Dautenhahn K, Dubowski J. Does appearance matter in the interaction of children with autism with a humanoid robot? Interact Stud. 2006;7(3):509–42.

    Article  Google Scholar 

  125. Robins B, Dautenhahn K, Te Boekhorst R, Billard A. Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills? Univers Access Inf Soc. 2005;4(2):105–20.

    Article  Google Scholar 

  126. Rosset D, Rondan C, Fonseca D, Santos A, Assouline B, Deruelle C. Typical emotion processing for cartoon but not for real faces in children with autistic spectrum disorders. J Autism Dev Disord. 2008;38(5):919–25.

    Article  PubMed  Google Scholar 

  127. Sadeghipour A, Kopp S. Embodied gesture processing: motor-based integration of perception and action in social artificial agents. Cognit Comput. 2011;3(3):419–35.

    Article  PubMed Central  PubMed  Google Scholar 

  128. Scassellati B. Imitation and mechanisms of joint attention: a developmental structure for building social skills on a humanoid robot. In: Computation for metaphors, analogy, and agents. Springer, Berlin; 1999; p. 176–195.

  129. Scassellati B. Foundations for a Theory of Mind for a Humanoid Robot. PhD thesis, Massachusetts Institute of Technology; 2001.

  130. Scassellati B. How social robots will help us to diagnose, treat, and understand autism. In: Robotics research. Springer, Berlin; 2007; p. 552–563.

  131. Scassellati B, Admoni H, Mataric M. Robots for use in autism research. Ann Rev Biomed Eng. 2012;14:275–94.

    Article  CAS  Google Scholar 

  132. Serret S. Jestimule, a serious game for autism spectrum disorders. Neuropsychiatr Enfance Adolesc. 2012;60(5):59.

    Article  Google Scholar 

  133. Simon M, Canet P, Soussignan R. L’enfant face à des expressions robotiques et humaines. Enfance. 2007;59(1):59–70.

    Article  Google Scholar 

  134. Sisbot E, Marin L, Alami R. Spatial reasoning for human robot interaction. In: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on. IEEE; 2007; p. 2281–2287.

  135. Steil J, Röthling F, Haschke R, Ritter H. Situated robot learning for multi-modal instruction and imitation of grasping. Robot Auton Syst. 2004;47(2):129–41.

    Article  Google Scholar 

  136. Stribling P, Rae J, Dickerson P. Using conversation analysis to explore the recurrence of a topic in the talk of a boy with an autism spectrum disorder. Clin Linguist Phon. 2009;23(8):555–82.

    Article  PubMed  Google Scholar 

  137. Strickland D. Brief report: two case studies using virtual reality as a learning tool for autistic children. J Autism Dev Disord. 1996;26(6):651–9.

    Article  CAS  PubMed  Google Scholar 

  138. Sun X, Nijholt A. Multimodal embodied mimicry in interaction. In: Analysis of Verbal and Nonverbal Communication and Enactment. The Processing Issues. Springer; 2011; p. 147–153.

  139. Takacs B. Special education and rehabilitation: teaching and healing with interactive graphics. IEEE Comput Graph Appl. 2005;25(5):40–8.

    Article  PubMed  Google Scholar 

  140. Tapus A, Mataric M, Scassellati B. Socially assistive robotics. IEEE Robot Autom Mag. 2007;14(1):35.

    Article  Google Scholar 

  141. Tartaro A, Cassell J. Authorable virtual peers for autism spectrum disorders, conference on human factors in computing systems. CHI ’07, San Jose, CA, USA, 2007;p. 1677–1680.

  142. Thill S, Pop C, Belpaeme T, Ziemke T, Vanderborght B. Robot-assisted therapy for autism spectrum disorders with (partially) autonomous control: challenges and outlook. Paladyn. 2012;3(4):209–17.

    Article  Google Scholar 

  143. Thorndike E. Animal intelligence: An experimental study of the associative processes in animals. Psychol Monogr General Appl, 1898;2(4):i–109.

  144. Tomasello M. Joint attention as social cognition. Joint attention: its origins and role in development; 1995. p. 103–130.

  145. Tomasello M, Farrar M. Joint attention and early language. Child Dev, 1986; p. 1454–1463.

  146. Trepagnier C, Michael R. Telerehabilitation and virtual reality technology for rehabilitation: preliminary results. Proceedings of the 1999 International Technology and Persons with Disabilities Conference, 1999.

  147. Varni G, Volpe G, Camurri A. A system for real-time multimodal analysis of nonverbal affective social interaction in user-centric media. IEEE Trans Multimed. 2010;12(6):576–90.

    Article  Google Scholar 

  148. Vinciarelli A, Pantic M, Bourlard H. Social signal processing: survey of an emerging domain. Image Vis Comput. 2009;27(12):1743–59.

    Article  Google Scholar 

  149. Vismara L, Rogers S. Efficacy of the early start denver model parent intervention for toddlers with asd delivered via internet technology. Philadelphia (USA): Oral presentation at International Meeting for Autism Research; 2010.

  150. Wainer J, Ferrari E, Dautenhahn K, Robins B. The effectiveness of using a robotics class to foster collaboration among groups of children with autism in an exploratory study. Personal Ubiquitous Comput. 2010;14(5):445–55.

    Article  Google Scholar 

  151. Wallon H. De l’acte à la pensée 1942.

  152. Wang M, Reid D. Virtual reality in pediatric neurorehabilitation: attention deficit hyperactivity disorder. Autism and cerebral palsy. Neuroepidemiology. 2011;36:218.

    Article  Google Scholar 

  153. Weissman O, Delaherche E, Rondeau M, Chetouani M, Cohen D, Feldman R. Oxytocin shapes parental motion characteristics during parent-infant interaction. Biol Lett, page in revision.

  154. Welch K, Lahiri U, Warren Z, Sarkar N. An approach to the design of socially acceptable robots for children with autism spectrum disorders. Int J Soc Robot. 2010;2(4):391–403.

    Article  Google Scholar 

  155. Whiten A, Ham R. On the nature and evolution of imitation in the animal kingdom: reappraisal of a century of research. Adv Study Behav. 1992;21:239–83.

    Article  Google Scholar 

  156. Winters J. Telerehabilitation research: emerging opportunities. Annu Rev Biomed Eng. 2002;4:287320.

    Article  Google Scholar 

  157. Yucel Z, Salah A, Merigli C, Meriçli T. Joint visual attention modeling for naturally interacting robotic agents. In: Computer and Information Sciences, 2009. ISCIS 2009. 24th International Symposium on. IEEE; 2009; pages 242–247.

Download references

Acknowledgments

This study was supported by a grant from the European Commission (FP7: Michelangelo under Grant agreement n 288241) and the fund “Entreprendre pour aider.” The funding agencies and the University were not involved in the study design, collection, analysis and interpretation of data, writing of the paper or the decision to submit the paper for publication. We would like to thank MICHELANGELO Study Group (S. Bonfiglio, K. Maharatna, E. Tamburini, A. Giuliano, M. Donnelly) for interesting discussions.

Author information

Authors and Affiliations

  1. Institut des Systemes Intelligents et de Robotique, CNRS UMR 7222, Universite Pierre et Marie Curie, Paris, France

    Sofiane Boucenna, Elodie Tilmont, David Cohen & Mohamed Chetouani

  2. Division of Child Neurology and Psychiatry, University of Pisa, Stella Maris Scientific Institute, Calambrone, Italy

    Antonio Narzisi & Filippo Muratori

  3. Department of Child and Adolescent Psychiatry, AP-HP, Groupe Hospitalier Piti-Salpltrire, Universit Pierre et Marie Curie, Paris, France

    Elodie Tilmont & David Cohen

  4. CNR, Rome, Italy

    Giovanni Pioggia

Authors
  1. Sofiane Boucenna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonio Narzisi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elodie Tilmont
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Filippo Muratori
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Giovanni Pioggia
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. David Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mohamed Chetouani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sofiane Boucenna.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Boucenna, S., Narzisi, A., Tilmont, E. et al. Interactive Technologies for Autistic Children: A Review. Cogn Comput 6, 722–740 (2014). https://doi.org/10.1007/s12559-014-9276-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12559-014-9276-x

Keywords

Search

Navigation